Antibodies (immunoglobulin, Ig) exist in blood and interstitial fluid of animals, which belong to a kind of glycoprotein produced by B lymphocytes in immune response to antigens, Antibodies are widely used in biological studies and clinic treatment on account of their high affinity for antigens. Especially under gradual maturity of genetic technology and clone technology, monoclonal antibodies (mAbs) have become effective therapeutics for inflammation, tumor, and infectious diseases. Up to now, there're approximately 20 mAbs that have been approved by FDA and at least 300 are under research and development. The output value of mAb-based drugs had reached 20.6 billion dollars in 2006. The increasing significance of antibodies in medical treatment calls for an urgent need of an efficient, stable, and low-cost manufacturing technique. Due to the complexity of antibody expression and high-quality standard required for pharmaceutical antibodies, antibody purification has become a critical step in the whole production process. IgG is the main component of Igs in blood serum, accounting for 75% of the total Igs, and also has the highest market demand among all Igs.
Antibody purification is often conducted by multi-steps including salting-out, gel-filtration chromatography, hydrophobic interaction chromatography, and ion-exchange chromatography and affinity chromatography. The feature of efficient and specific purification of target protein has made affinity chromatography into one of the most commonly used chromatographic methods in later period of antibody purification. Affinity chromatography makes use of the affinity ligand that specifically and reversibly binds the target molecule thus to separate it from complicated biological samples. It has the advantage of high selectivity and high purification efficiency. The purification performance of affinity chromatography depends on the affinity between the ligand and the target molecule. Therefore, the exploitation of suitable affinity ligand targeting specific molecule is the priority of building an affinity chromatographic system.
Staphylococal Protein A (SpA), protein G, and protein L have been widely used as affinity ligands for producing high-purity antibodies. Such ligands possess high selectivity, nonetheless need harsh elution condition, which tends to denature target proteins and causes ligands to fall off, leading to a low adsorption capacity. Moreover, protein ligands are difficult to prepare, costly, and are prone to lose some activity upon immobilization. These disadvantages have limited the application of the above protein ligands.
The research into affinity peptide ligands began with Geysen's study of synthetic peptide library in 1986, who proposed that the short peptide containing key residues could simulate the protein determinant. And in most cases, the non-covalent interactions between a few of key residues and the target molecule constitute the main interaction force for the complex binding. The two viewpoints have laid the theoretical basis for affinity peptide ligands. Firstly, peptide ligands are usually comprised of a few amino acids and therefore have little chance of causing immunogenic responses in use. Secondly, peptide ligands have a small molecular size. So even if they fall off from the stationary phase and mix with the products, it is easy to remove them from the end-products. Finally, the peptide ligands interact with target protein in mild conditions, which can make it easier to control the separation conditions and avoid the denaturation of target proteins. Compared with the high affinity ligands such as protein ligands, peptide ligands also exhibit sufficient affinity for binding target proteins. Besides, the conformation and physicochemical properties of peptide ligands are more stable than those of protein ligands, and thus the ligands can sustain harsh acid or base elution and regeneration conditions during the separation process, realizing the large-scale aseptic manufacturing that meets GMP requirements. In recent years, some peptide ligands with great purification performance for antibodies have sprung up, such as TG19318, Peptide H, Mabsorbent A1P and A2P, 8/7, and linear peptide ligand (HWRGWV etc.).
Although affinity peptide ligands have such many advantages, there are only a limited number of peptides that have affinity for specific target proteins in nature. In addition, although the above-mentioned micromolecule ligands have a huge superiority in antibody purification, they have some deficiencies compared with SpA affinity resin, like weak specificity and affinity, etc. Therefore, research in screening and designing ligands for affinity chromatography is vital. The question about how to choose proper peptides as affinity ligands and how to improve the affinity and selectivity of the peptide ligands is crucial in the application of affinity chromatography. The present screening and designing methods are mainly divided into two kinds of approaches, namely experimental screening and rational design. Experimental screening is based on the combinatorial library technology to conduct high-throughput screening. According to the different ways of constructing peptide library, the screening methods for affinity ligands are mainly divided into combinatorial chemistry synthetic peptide library technology, such as TG19318/D-TG19318, Peptide H, Mabsorbent A1P and A2P, and 8/7 mentioned above; phage display peptide library technology, such as HWRGWV, HYFKFD, and HFRRHL; and ribosome display peptide library technology. Rational design is mainly based on the structure and properties of the target protein or the known ligands to design new ligands. As the computer technique, computational chemistry, and medicinal chemistry develop, the design of affinity ligands has entered the rational design phase dominated by computer aided design. The various virtual screening and rational design methods of computer aided ligand design include molecular docking, 3D-QSAR, pharmacophore model, molecular dynamics (MD) simulation, and de novo design, etc.
Molecular docking involves two molecules recognizing each other through geometric matching and energy matching. Molecular docking is a calculation process in which the ligand is put on the binding site of the target protein, and the binding strength is evaluated via the criteria of geometric complementarity, energy complementarity, and chemical environment complementarity. Meanwhile, the best binding conformation can be found. Since molecular docking has considered the interaction between the target protein and the ligand, so in principle, molecular docking is a direct design method on the basis of the receptor. In recent years, as the protein crystal structure data grows rapidly and the small molecule databases updates constantly, molecular docking has become the most important structure-based design method. The common softwares include DOCK, Autodock, and FlexX, etc.
Molecular dynamics (MD) simulation is a kind of molecular simulation method on the basis of Newtonian mechanics. It has been used for studying the particle movement in many-particle system. The basic procedure in MD simulation can be divided into four steps: (1) initialization; (2) calculation of atomic force; (3) updating the atom coordinates and speed; (4) analysis of trajectory. According to the atom coordinates, speed, and force of the last step, the coordinates and speed of next step can be obtained. Steps (2) and (3) are repeated to obtain the change of physicochemical properties in the system with simulation time. The softwares commonly used in MD simulation include GROMACS, NAMD, AMBER, and CHARMM, etc. Based on the analysis of MD simulation trajectories, we can study the physicochemical properties of the simulation system, such as conformation, energy, kinetic property, and the interaction force between the ligand and the target protein, etc.
Combination of a few of rational design methods and proper combination strategy can reduce the cost and realize higher-accuracy ligand design. In early phase, some methods of rapid speed but limited accuracy can be used to enrich potential candidates, like molecular docking. Then, some methods with more calculation but also more accuracy can be adopted to further select the best ligand molecules, like MD simulation. In the final phase, experiments which are time-consuming and costly are used to conduct the last verification.